In commercial mobile products such as, for example, cell phones, CMOS RWB imaging sensor has been recently introduced as the image sensor for the cell phone's camera. The RWB sensor includes a Color Filter Array (CFA) of red, white, and blue color filters arranged in a Bayer color pattern. The CMOS RWB sensor has been known to produce better image quality in low light environment with lower noise compared to the conventional CMOS RGB sensor counterpart. In construction, the CMOS RWB sensor differs from the traditional Bayer pattern-based CMOS RGB sensor in that the green filter in the RGB CFA is replaced with a white (or clear) filter in the RWB CFA. As a result, the RWB sensor allows more photons to reach the photon-sensitive sites (also referred to as “photo-sites”), which, in turn, increases the sensor's Signal-to-Noise Ratio (SNR). On the other hand, due to the broadband (or panchromatic) spectral response of the white filter, the associated Color Correction Matrix (CCM)—which is commonly used to convert colors from the camera color space to a standard color space such as, for example, the Standard RGB (sRGB) color space—has large off-diagonal entries. These large entries lead to a vast amplification of noise during the color correction phase in the image processing pipeline in the CMOS RWB sensor. As a consequence, the increased Luminance SNR (YSNR) in the raw RWB image—because of more photons collected by the photo-sites—diminishes and the noise becomes higher than that in the corresponding traditional RGB image. This is the main reason why RWB sensor was not previously vastly adapted in commercial products.
However, recent developments in Image Signal Processing (ISP) have addressed this noise amplification issue and, as a result, now the YSNR of an RWB sensor can be raised to a decent level. For example, the Clarity+ ISP application developed by Aptina Imaging Corporation of San Jose, Calif., USA (now part of ON Semiconductor of Phoenix, Ariz., USA) can achieve +3 dB of YSNR increase for an RWB sensor under low light. This ISP application correlates the noise in the three color channels—R, W, and B. Thus, when the image is converted to the standard color space by the CCM of the RWB sensor, the noise will not be amplified as much. As a result, the final image by the RWB sensor has less noise than that by the comparable RGB sensor.
Moreover, current RWB sensors may suffer from colorblindness and chromatic aberration artifacts. Colorblindness arises because an RWB sensor can be “blind” to certain color edges which an RGB sensor has no problem distinguishing. On the other hand, chromatic aberration arises because red, green, and blue lights have different diffraction ratios and, hence, they may focus in front of/back to the image plane, or at different locations even if they all focus on the image plane. Chromatic aberration may be present, especially in the absence of a sophisticatedly-designed lens to completely eliminate such aberration. When chromatic aberration occurs, the white light signal—containing the red, green, and blue components—will be blurry because of the mixing of lights at different focus points. On the other hand, the traditional RGB sensor has lower chromatic aberration than the RWB sensor.